Multidisciplinary Data Analysis Services

IraDigiTech is globally known Data Analysis Consultancy Services where the professionals uses the Latest tools and software for data processing.
best data analysis services in chandigarh, Data Analysis Consultancy Services
Data Analysis Consultancy Services

Best Data Analysis Consultancy Services

Microsoft Excel 365 Data Analysis

  • Microsoft Excel is one of the most widely used programmes for data analysis.
  • Build presentation ready dashboards with spreadsheet functions that can manage and organise large data sets.
  • It also has graphing tools and computing capabilities, such as automated summation, or “AutoSum.” Learn how to utilise pivot tables and pivot charts in Excel to automate your process.
  • Recognise and comprehend the fundamentals of data analysis. This includes Analysis ToolPak, which offers statistical analysis, variance analysis, and regression data analysis tools.
  • Excel’s ease of use and versatility make it a powerful tool for managing, sorting, filtering, cleaning, analysing, visualising data, and strategic use as a BI tool.
  • If you are just getting started in data science, you should consider learning more about Excel to get ready for your future profession.

Python

  • Python is frequently ranked as the most popular programming language in the world today.
  • Unlike other programming languages, Python is relatively easy to learn and can be used for a variety of tasks, including software, web development, and data analysis.
  • Python is used in the data world to streamline, model, visualise, and analyse data using its built-in data analytics tools.
  • One of the main features of Python that appeals to data analytics professionals is its many libraries, like Pandas and Numpy, which offer a variety of powerful tools for many analytics needs.
  • Utilise Python’s well-known Pandas module to perform a wide range of data operations, such as pivoting, joining, grouping, and more.

R

  • R is an open-source programming language used for statistical computing and graphics.
  • It is regarded as one of the most important programming languages used in data analysis.
  • R is typically used for statistical analysis, data visualisation, and data manipulation.
  • Its statistical focus makes it well-suited to statistical calculations.
  • Its visualisation tools make it an excellent language for creating compelling graphics.

IBM SPSS Statistics

  • Statistical software platform IBM® SPSS® Statistics is highly effective.
  • A wide spectrum of academics utilise SPSS, which stands for Statistical Package for the Social Sciences, to analyse complex statistical data.
  • Perform the basic data analysis procedures: Frequencies, Descriptives, Explore, Means, Crosstabs
  • Perform simple operations with data: define variables, recode variables, create dummy variables, select and weight cases, split files
  • Built the most useful charts in SPSS: column charts, line charts, scatterplot charts, boxplot diagrams
  • Test the hypothesis of normality (with numeric and graphic methods)

PLS-SEM

  • Partial Least Squares Structural Equation Modelling, or PLS-SEM, is a superior option for investigating and forecasting non-normal, categorical, or ordinal data, small sample sizes, intricate models with numerous variables and indicators, higher-order constructs, formative assessment, and managing mediation and moderation effects.
  • PLS-SEM has recently drawn more attention in practise and study fcategorical,ty of fields, including the political, social, engineering, medical, marketing, information systems, management, and psychology.
  • PLS-SEM allows researchers to develop and evaluate complicated cause-effects connection models, with both latent (shown graphically as circles) and observable (represented graphically as rectangles) variables.
  • Latent variables refer to phenomena that are not directly observable, such as attitudes, intents, and perceptions, and are therefore unseen.
  • In a statistical model, the latent variables are represented by the observed variables (such as secondary data or questionnaire answers).

AMOS

  • Amos is a powerful structural equation modelling (SEM) program
  • Extends the capabilities of common multivariate analysis techniques
  • Create behavioral and attitude models
  • More precisely depict complex interactions
  • Part of SPSS Statistics Premium
  • Available as a stand-alone program
  • Part of SPSS Statistics’ Base, Standard, and Professional editions
  • Simple data entry
  • Enter a model using a table akin to a spreadsheet (no programming needed)
  • Includes Bayesian estimation, latent class analysis, and other features
  • Discover hidden variables through path analysis and structural equation modeling and it can support your business needs

MATLAB

  • MATLAB is a tool used by scientists and engineers to organise, clean, and analyse large, complicated data sets from a variety of industries, including finance, climatology, predictive maintenance, and medical research.
  • MATLAB offers preprocessing tools and data formats intended for scientific and engineering data
  • Data visualisations that are highly customisable and interactive
  • Tasks in Live Editor and apps that support interactive data preparation, cleaning, and coding
  • Thousands of preconfigured routines for signal processing, machine learning, and statistical analysis
  • Improved performance with only minor code modifications, extra hardware, voluminous, and expertly authored documentation
  • Big data analysis expanded without significant code modifications
  • Without requiring manual recoding of methods, automatic packaging of analysis into freely distributable software components or embeddable source code
  • Automatically created shareable reports based on your analysis